The underlying statistical distribution for a variable or attribute process may be
determined by analyzing independent and identically distributed data drawn from the
process under observation. An understanding of the underlying distribution is essential to
the development and use of inferential statistical methods. The statistical validity of
studies depends on verifiable confirmation of the underlying distribution properties.
Risk analysis on the probability of occurrence of various events can be calculated in
order to place statistical limits on the possibility or feasibility of given designs with
respect to safety and applicability to a given purpose.
Studies to determine if the effect of a given variable is statistically significant or
statistically valid require the analysis of multipopulation or multivariate data.
Environmental impact reports and analysis consist of statistical data and results to
support given claims. It is important to confirm or verify the statistical validity of
such claims, to recognize incorrectly processed data, or to offer statistically valid
counter-claims using a study's own data.
Custom statistical software can be developed dedicated to a particular use or purpose
that will simplify data gathering and analysis of environmental data to be used to support
certain environmental claims.